Focal Article: Maladaptive Personality at Work: Exploring the Darkness.

Important changes in how personality is conceptualized and measured are occurring in clinical psychology. We focus on one aspect of this work that industrial psychologists have been slow to embrace, namely, a new trait model that can be viewed as a maladaptive counterpart to the big five. There is a conspicuous absence of work psychology research emerging on this trait model despite important implications for how we understand personality at work. We discuss objections to the trait model in a work context and offer rejoinders that might make researchers and practitioners consider applying this model in their work. We hope to stimulate discussion of this topic to avoid an unnecessary bifurcation in the conceptualization of maladaptive personality between industrial and clinical settings

The importance of isomorphism for conclusions about homology: A Bayesian multilevel structural equation modeling approach with ordinal indicators

We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes or using informative priors

Can faking be measured with dedicated validity scales? Within Subject Trifactor Mixture Modeling applied to BIDR responses

A sample of 516 participants responded to the Balanced Inventory of Desirable Responding (BIDR) under answer honest and instructed faking conditions in a within-subjects design. We analyse these data with a novel application of trifactor modeling that models the two substantive factors measured by the BIDR – Self-Deceptive Enhancement (SDE) and Impression Management (IM), condition-related common factors and item specific factors. The model permits examination of invariance and change within subjects across conditions. Participants were able to significantly increase their SDE and IM in the instructed faking condition relative to the honest response condition. Mixture modeling confirmed the existence of a theoretical two-class solution comprised of approximately two thirds of ‘compliers’ and one third of ‘non-compliers’. Factor scores had good determinacy and correlations with observed scores were near unity for continuous scoring, supporting observed score interpretations of BIDR scales in high stakes settings. Correlations were somewhat lower for the dichotomous scoring protocol. Overall, results show that the BIDR scales function similarly as measures of socially desirable functioning in low and high stakes conditions. We discuss conditions under which we expect these results will and will not generalise to other validity scales

Robots are judging me: Perceived fairness of algorithmic recruitment tools

Recent years have seen rapid advancements in selection assessments, shifting away from human and toward algorithmic judgments of candidates. Indeed, algorithmic recruitment tools have been created to screen candidates’ resumes, assess psychometric characteristics through game-based assessments, and judge asynchronous video interviews, among other applications. While research into candidate reactions to these technologies is still in its infancy, early research in this regard has explored user experiences and fairness perceptions. In this article, we review applicants’ perceptions of the procedural fairness of algorithmic recruitment tools based on key findings from seven key studies, sampling over 1,300 participants between them. We focus on the sub-facets of behavioral control, the extent to which individuals feel their behavior can influence an outcome, and social presence, whether there is the perceived opportunity for a social connection and empathy. While perceptions of overall procedural fairness are mixed, we find that fairness perceptions concerning behavioral control and social presence are mostly negative. Participants feel less confident that they are able to influence the outcome of algorithmic assessments compared to human assessments because they are more objective and less susceptible to manipulation. Participants also feel that the human element is lost when these tools are used since there is a lack of perceived empathy and interpersonal warmth. Since this field of research is relatively under-explored, we end by proposing a research agenda, recommending that future studies could examine the role of individual differences, demographics, and neurodiversity in influencing fairness perceptions of algorithmic recruitment

Forced-Choice Assessment of Work-Related Maladaptive Personality Traits: Preliminary Evidence From an Application of Thurstonian Item Response Modeling

This article describes an investigation of whether the forced-choice response format is a viable method for assessment of maladaptive traits. Thurstonian item response models were fitted to a data set of 420 responses from working adults to a broad-range maladaptive personality inventory. The Thurstonian model fit was compared with confirmatory factor analysis fit to the same item content but arranged in a single-stimulus design and administered to the same sample. Mono-trait-hetero method correlations indicated corresponding traits in the two formats overlapped substantially, although they did not measure equivalent constructs. A better statistical fit and higher factor loadings for the Thurstonian item response model, coupled with a clearer conceptual alignment to the theoretical trait definitions, suggested that the single-stimulus item responses were influenced by biases that the independent clusters confirmatory factor analysis measurement model did not account for. We recommend use of forced choice designs and appropriate item response modeling techniques for personality questionnaire applications in industrial psychology, especially when assessing maladaptive traits

Can faking be measured with dedicated validity scales? Within Subject Trifactor Mixture Modeling applied to BIDR responses

A sample of 516 participants responded to the Balanced Inventory of Desirable Responding (BIDR) under answer honest and instructed faking conditions in a within-subjects design. We analyse these data with a novel application of trifactor modeling that models the two substantive factors measured by the BIDR – Self-Deceptive Enhancement (SDE) and Impression Management (IM), condition-related common factors and item specific factors. The model permits examination of invariance and change within subjects across conditions. Participants were able to significantly increase their SDE and IM in the instructed faking condition relative to the honest response condition. Mixture modeling confirmed the existence of a theoretical two-class solution comprised of approximately two thirds of ‘compliers’ and one third of ‘non-compliers’. Factor scores had good determinacy and correlations with observed scores were near unity for continuous scoring, supporting observed score interpretations of BIDR scales in high stakes settings. Correlations were somewhat lower for the dichotomous scoring protocol. Overall, results show that the BIDR scales function similarly as measures of socially desirable functioning in low and high stakes conditions. We discuss conditions under which we expect these results will and will not generalise to other validity scales

The NEO-PI-R: Factor structure and gender invariance from exploratory structural equation modelling analyses in a high-stakes setting

This study presents new analyses of NEO Personality Inventory–Revised (NEO-PI-R) responses collected from a large British sample in a high-stakes setting. The authors show the appropriateness of the five-factor model underpinning these responses in a variety of new ways. Using the recently developed exploratory structural equation modeling (ESEM) technique, the authors show that model fits improve markedly over conventional confirmatory factor analyses (CFA) of the same data set, but that (a) factor interpretations do not change under ESEM analyses, (b) ESEM factor scores, just like CFA factors scores, correlate at near unity with sums of observed scores, (c) NEO-PI-R facets under ESEM analyses are invariant across gender, and (d) ESEM highlights the inappropriateness of alpha and beta as a higher order representation of NEO-PI-R facets, whereas a CFA approach might lead researchers to believe in the appropriateness of these higher order factors. These results, coupled with the existing validity evidence for the NEO-PI-R, suggest that the five-factor structure is the most parsimonious structure for summarizing NEO-PI-R responses from high-stakes settings in the United Kingdom

Preliminary psychometric properties of the Acceptance and Action Questionnaire – II: A revised measure of psychological flexibility and acceptance.

The present research describes the development and psychometric evaluation of a second version of the Acceptance and Action Questionnaire (AAQ-II), which assesses the construct referred to as, variously, acceptance, experiential avoidance and psychological inflexibility. Results from 2,816 participants across six samples indicate the satisfactory structure, reliability, and validity of this measure. For example, the mean alpha coefficient is .84 (.78 - .88), and the 3- and 12-month test-retest reliability is .81 and .79, respectively. Results indicate that AAQ-II scores concurrently, longitudinally, and incrementally predict a range of outcomes, from mental health to work absence rates,that are consistent with its underlying theory. The AAQ-II also demonstrates appropriate discriminant validity. The AAQ-II appears to measure the same concept as the AAQ-I (r = .97), but with better psychometric consistency